Computational approaches to the inference of biological network connectivity

2005 2005

Other formats: Order a copy

Abstract (summary)

The phenotype of a unicellular organism is determined by an integrated network of genes, proteins, and metabolites that participate in reciprocal regulatory relationships. Creating a quantitative description of this network is essential to understanding, predicting and manipulating cellular behavior. A first step toward this goal is deciphering the connectivity of the network, i.e., the pattern of interactions among its components, and its general organizational features. Given the complexity of this task, it is convenient to view the integrated network as a group of superimposed subnetworks, including the gene regulatory, protein, and metabolic networks. This thesis addresses the inference of connectivity in the gene and protein networks of Saccharomyces cerevisiae and Pseudomonas aeruginosa.

It is widely believed that biological networks are organized into functional modules, defined here as groups of genes, proteins, and other small molecules that participate in common subcellular processes. Chapter 2 presents a computational method to identify transcriptional coordination among predefined functional modules of genes in S. cerevisiae. Two modules are said to be coordinated by a particular transcription factor if it confers a distinct expression profile on its target genes in each module. The method was applied to a variety of module pairs to reveal a global network of functional coordination in yeast.

Chapter 3 describes an algorithm that searches the S. cerevisiae protein-protein interaction network for signal transduction pathways whose components are encoded by coexpressed genes. This enables the discovery of known and novel linear signal transduction pathways. When linear pathways with common endpoints are combined, the resulting network represents the complex interactions underlying signal transduction more fully than a traditional linear representation.

Chapter 4 describes the identification of putative transcription factor binding motifs that shape the topology of the quorum sensing gene regulatory network in the pathogenic bacterium P. aeruginosa. The approach identified novel, putative motifs, and variants of a motif known to function in quorum sensing. These motifs may imbue quorum-sensing regulation with signal and/or temporal specificity.

Indexing (details)

0369: Genetics
0308: Biostatistics
0786: Biophysics
Identifier / keyword
Biological sciences; Biological network connectivity; Metabolic networks; Protein networks; Quorum sensing; Systems biology
Computational approaches to the inference of biological network connectivity
Petti, Allegra Adele
Number of pages
Publication year
Degree date
School code
DAI-B 66/05, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
9780542115578, 0542115573
Church, George M.
Harvard University
University location
United States -- Massachusetts
Source type
Dissertations & Theses
Document type
Dissertation/thesis number
ProQuest document ID
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
Access the complete full text

You can get the full text of this document if it is part of your institution's ProQuest subscription.

Try one of the following:

  • Connect to ProQuest through your library network and search for the document from there.
  • Request the document from your library.
  • Go to the ProQuest login page and enter a ProQuest or My Research username / password.